Genome and Phenome to Define Disease Risk with Antinuclear Antibodies

项目总结 抗核抗体(ANA)是一种与自身抗原发生反应的抗体，通常用于帮助 诊断系统性红斑狼疮。因为几乎每个患者的检测都是阳性(ANA+) 对于SLE--甚至在疾病发生前几年--ANA阳性测试实际上被认为是诊断SLE的必要条件 红斑狼疮的诊断。然而，该检测在很大一部分普通人群(~20%)中也呈阳性。 虽然这些ANA+的人中很少有人在未来会发展为自身免疫性疾病，但临床上 ANA阳性对没有自身免疫性疾病的人的影响尚不清楚。第二个问题是 在没有自身免疫性疾病的人中常见的ANA+会导致不正确的问题 诊断系统性红斑狼疮，特别是如果ANA阳性的人也有关节或肌肉疼痛的话。为了更准确地诊断 为了防止SLE和误诊，我们需要解决两大知识差距：1)我们需要了解 ANA阳性检测对没有自身免疫性疾病的人的重要性；以及2)我们需要能够 预测哪些ANA检测呈阳性的人已经或将会患上SLE。 在这项研究中，我们将评估临床和遗传信息可以：1) 确定ANA阳性在没有自身免疫性疾病的人中的临床后果，以及2) 改进风险预测，以区分SLE风险增加的人群。因此，我们提出了三个 具体目标：1)检验没有自身免疫性疾病的人的抗核抗体阳性与 具有临床表型(使用临床和遗传学方法)；2)检验以下假设 预测模型将准确区分早期SLE患者或有SLE风险的患者 那些抗核抗体阳性但没有自身免疫性疾病的人；以及3)检验以下假设： 遗传和临床信息将准确区分有SLE风险的患者。为了达到这些目标，我们 将使用范德比尔特大学医学中心生物库(BioVU)和未识别的电子健康记录 (EHR)使用最先进的基因技术和数据驱动创建遗传和临床风险评分 预测工具。 这些研究的结果可以：a)确定ANA阳性且没有自身免疫性疾病的人 有改变的疾病风险，可以用来指导卫生保健决策；和b)改变对 通过提高早期SLE诊断的准确性，识别未来风险最高的患者。这些 这些发现将帮助临床医生更早地开始治疗，以控制炎症和防止损害，并将 减少误诊率，从而保护患者免受不必要的治疗 效果。

PROJECT SUMMARY Antinuclear antibodies (ANA) are antibodies that react against self-antigens and are commonly used to help diagnose systemic lupus erythematosus (SLE). Because the test is positive (ANA+) in almost every patient with SLE— even years before the disease onset—a positive ANA test is considered virtually a requisite for the diagnosis of SLE. However, the test is also positive in a large proportion of the general population (~20%). Although very few of these ANA+ individuals will develop an autoimmune disease in the future, the clinical impact of a positive ANA in people without autoimmune disease is unknown. A second problem is that the common occurrence of ANA+ in people without autoimmune disease can lead to the problem of an incorrect diagnosis of SLE, particularly if an ANA+ person also has joint or muscle pain. To more accurately diagnose SLE and prevent false diagnoses, we need to address two major knowledge gaps: 1) we need to understand the importance of a positive ANA test in people without an autoimmune disease; and 2) we need to be able to predict which people with a positive ANA test have or will develop SLE. In this study we will evaluate the overarching hypothesis that clinical and genetic information can: 1) define the clinical consequences of positive ANA in people without autoimmune diseases, and 2) improve risk prediction to differentiate people with increased risk of SLE. Thus, we proposed three Specific Aims: 1) test the hypothesis that a positive ANA in people without autoimmune disease is associated with clinical phenotypes (using a clinical and a genetic approach); 2) test the hypothesis that a clinical prediction model will accurately discriminate patients with early SLE or who are at risk for SLE from among those with positive ANA without an autoimmune disease; and 3) test the hypothesis that the combination of genetic and clinical information will accurately discriminate patients at risk for SLE. To address these aims, we will use the Vanderbilt University Medical Center Biobank (BioVU) and de-identified electronic health records (EHR) to create genetic and clinical risk scores using state-of-the-art genetic techniques and data-driven prediction tools. The results of these studies could: a) define whether people with a positive ANA and no autoimmune disease have an altered risk of illnesses that could be used to guide health-care decisions; and b) transform the care of SLE by improving the accuracy of early-stage SLE diagnosis and identify patients at highest future risk. These findings will help clinicians start treatment earlier to control inflammation and prevent damage and will decrease the rates of misdiagnosis, thereby protecting patients from unnecessary therapies and their side effects.